Quantitative cardiac results for ventricular function is crucial information and plays a major role in therapeutic decision making, monitoring disease progression, and is of high value concerning diagnostic and prognostic evaluations. However, post-processing medical images to obtain this actionable data is a time-consuming, costly, and laboriously repetitive process despite available semi-automated border detection tools. The current standard practice of manually producing the contours for functional cardiac magnetic resonance imaging (MRI) cases takes approximately 40 minutes and involves manually delineating specific regions of cardiac anatomy leading to inherent high observer-dependent variability. The issue is further perpetuated by advanced analyses such as Feature Tracking or Time-Volume curve quantification which may require hundreds of images to be contoured, unnecessarily requiring a significant amount of dedicated physician or technologist time.